激光与光电子学进展, 2018, 55 (11): 112001, 网络出版: 2019-08-14   

基于改进蜻蜓算法的多基地天波雷达定位模型 下载: 875次

Multi-Static Sky-Wave Over-the-Horizon Radar Location Model Based on Improved Dragonfly Algorithm
作者单位
江南大学物联网工程学院, 江苏 无锡 214122
引用该论文

宋萍, 刘以安. 基于改进蜻蜓算法的多基地天波雷达定位模型[J]. 激光与光电子学进展, 2018, 55(11): 112001.

Ping Song, Yian Liu. Multi-Static Sky-Wave Over-the-Horizon Radar Location Model Based on Improved Dragonfly Algorithm[J]. Laser & Optoelectronics Progress, 2018, 55(11): 112001.

参考文献

[1] 韩彦明. 天波超视距雷达无源信标修正方法研究[D]. 南京: 南京理工大学, 2010: 1- 2.

    Han YM. Research on passive beacon correcting method of OTH radar[D]. Nanjing: Nanjing University of Science and Technology, 2010: 1- 2.

[2] 宋君, 赵正予, 周晨, 等. 多基高频天波超视距定位模型[J]. 系统工程与电子技术, 2011, 33(2): 272-275.

    Song J, Zhao Z Y, Zhou C, et al. Study on sky-wave over-the-horizon location model of high frequency multistatic system[J]. Systems Engineering and Electronics, 2011, 33(2): 272-275.

[3] 张佳智. 混合传播模式下目标定位修正方法研究[D]. 哈尔滨: 哈尔滨工业大学, 2016: 35- 40.

    Zhang JZ. Research on target localization correction methods under the mixes propagation mode[D]. Harbin: Harbin Institute of Technology, 2016: 35- 40.

[4] 周晨. 天波超视距雷达坐标配准与多径数据处理研究[D]. 武汉: 武汉大学, 2009: 86- 89.

    ZhouC. Research on skywave over-the-horizon radar coordinate registration and multipath data process[D]. Wuhan: Wuhan University, 2009: 86- 89.

[5] 宋君. 返回式电离层探测技术应用研究[D]. 武汉: 武汉大学, 2011: 89- 103.

    SongJ. Research on applications of backscatter ionospheric sounding techniques[D]. Wuhan: Wuhan University, 2011: 89- 103.

[6] 刘子威, 苏洪涛, 胡勤振. 天波超视距雷达中瞬态干扰定位方法研究[J]. 电子与信息学报, 2016, 38(10): 2482-2487.

    Liu Z W, Su H T, Hu Q Z. Transient interference localization method in the skywave over-the-horizon radar[J]. Journal of Electronics and Information Technology, 2016, 38(10): 2482-2487.

[7] 严韬, 陈建文, 罗欢.等. 新体制天波超视距雷达技术述评[J]. 飞航导弹, 2015( 3): 71- 76.

    YanT, Chen JW, LuoH, et al. Review on new system skywave over-the-horizon radar technology[J]. Winged Missiles Journal, 2015( 3): 71- 76.

[8] 卢琨. 分布式天波超视距雷达体制研究[J]. 现代雷达, 2011, 33(6): 16-19.

    Lu K. A study on distributed skywave over-the-horizon radar[J]. Modern Radar, 2011, 33(6): 16-19.

[9] 雷文英. 多站被动超视距雷达时差定位及相关问题研究[D]. 西安: 西安电子科技大学, 2014: 13- 15.

    Lei WY. Study on time-difference location and its related issues of over-the-horizon passive multistatic radar[D]. Xi'an:Xidian University, 2014: 13- 15.

[10] 陈百英. 远程超视距目标无源定位与跟踪技术[D]. 无锡: 江南大学, 2013: 8- 9.

    Chen BY. Research on the method of a single observer passive ranging and locating[D]. Wuxi: Jiangnan University, 2013: 8- 9.

[11] 陈伯孝, 张守宏. 基于综合脉冲与孔径技术的多基地“无源”定位系统[J]. 火控雷达技术, 2003, 32(1): 12-16.

    Chen B X, Zhang S H. Multistatic "passive" location system based on synthetic impulse and aperture radar (SIAR) techniques[J]. Fire Control Radar Technology, 2003, 32(1): 12-16.

[12] 胡炎, 张丕旭, 石章松. 基于Bowring公式的超视距目标定位算法实现[J]. 舰船电子工程, 2008, 28(11): 169-171.

    Hu Y, Zhang P X, Shi Z S. Implementation for location algorithm of targets beyond visual range based on Bowring formula[J]. Ship Electronic Engineering, 2008, 28(11): 169-171.

[13] 张晓玲. 无源时差定位技术在高频雷达中的应用[D]. 西安: 西安电子科技大学, 2013: 6- 9.

    Zhang XL. Application of passive TDOA location technology in HF radar[D]. Xi'an:Xidian University, 2013: 6- 9.

[14] Mirjalili S. Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems[J]. Neural Computing & Applications, 2016, 27(4): 1053-1073.

[15] Zhang Y Q, Wang X Y. Spatiotemporal chaos in mixed linear-nonlinear coupled logistic map lattice[J]. Physica A: Statistical Mechanics and Its Applications, 2014, 402(10): 104-118.

[16] Tizhoosh HR. Opposition-based learning: a new scheme for machine intelligence[C]∥International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, IEEE, 2005: 695- 701.

[17] 董文永, 康岚兰, 刘宇航, 等. 带自适应精英扰动及惯性权重的反向粒子群优化算法[J]. 通信学报, 2016, 37(12): 1-10.

    Dong W Y, Kang L L, Liu Y H, et al. Opposition-based particle swarm optimization with adaptive elite mutation and nonlinear inertia weight[J]. Journal on Communications, 2016, 37(12): 1-10.

[18] 康岚兰, 董文永, 宋婉娟, 等. 无惯性自适应精英变异反向粒子群优化算法[J]. 通信学报, 2017, 38(8): 66-78.

    Kang L L, Dong W Y, Song W J, et al. Non-inertial opposition-based particle swarm optimization with adaptive elite mutation[J]. Journal on Communications, 2017, 38(8): 66-78.

[19] 胡梦月, 胡志坚, 仉梦林, 等. 基于改进AdaBoost.RT和KELM的风功率预测方法研究[J]. 电网技术, 2017, 41(2): 536-542.

    Hu M Y, Hu Z J, Zhang M L, et al. Research on wind power forecasting method based on improved AdaBoost.RT and KELM algorithm[J]. Power System Technology, 2017, 41(2): 536-542.

[20] 王学武, 严益鑫, 丁冬雁, 等. 基于Lévy-PSO算法的焊接机器人避障路径规划[J]. 上海交通大学学报, 2016, 50(10): 1517-1520.

    Wang X W, Yan Y X, Ding D Y, et al. Collision free path planning for welding robot based on Lévy-PSO[J]. Journal of Shanghai Jiaotong University, 2016, 50(10): 1517-1520.

[21] 覃晖, 周建中, 王光谦, 等. 基于多目标差分进化算法的水库多目标防洪调度研究[J]. 水利学报, 2009, 40(5): 513-519.

    Qin H, Zhou J Z, Wang G Q, et al. Multi-objective optimization of reservoir flood dispatch based on multi-objective differential evolution algorithm[J]. Journal of Hydraulic Engineering, 2009, 40(5): 513-519.

[22] Huang G B, Zhu Q Y, Siew C K. Extreme learning machine: theory and applications[J]. Neurocomputing, 2006, 70: 489-501.

[23] 白俊健, 孙群, 井诗博, 等. 稳健极限学习机及其在近红外光谱分析中的应用[J]. 激光与光电子学进展, 2015, 52(10): 103002.

    Bai J J, Sun Q, Jing S B, et al. Robust extreme learning machine and its application in analysis of near infrared spectroscopy data[J]. Laser & Optoelectronics Progress, 2015, 52(10): 103002.

[24] 张海东, 李贵荣, 李若诚, 等. 近红外光谱结合极限学习机和GA-PLS算法检测普洱茶茶多酚含量[J]. 激光与光电子学进展, 2013, 50(4): 043001.

    Zhang H D, Li G R, Li R C, et al. Determination of tea polyphenols content in Puerh tea using near-infrared spectroscopy combined with extreme learning machine and GA-PLS algorithm[J]. Laser & Optoelectronics Progress, 2013, 50(4): 043001.

[25] 徐岩, 韦镇余. 一种改进的交通标志图像识别算法[J]. 激光与光电子学进展, 2017, 54(2): 021001.

    Xu Y, Wei Z Y. An improved traffic sign image recognition algorithm[J]. Laser & Optoelectronics Progress, 2017, 54(2): 021001.

[26] 杨锡运, 关文渊, 刘玉奇, 等. 基于粒子群优化的核极限学习机模型的风电功率区间预测方法[J]. 中国电机工程学报, 2015, 35(S1): 146-153.

    Yang X Y, Guan W Y, Liu Y Q, et al. Prediction intervals forecasts of wind power based on PSO-KELM[J]. Proceedings of the CSEE, 2015, 35(S1): 146-153.

[27] 黎珍惜, 黎家勋. 基于经纬度快速计算两点间距离及测量误差[J]. 测绘与空间地理信息, 2013, 36(11): 235-237.

    Li Z X, Li J X. Quickly calculate the distance between two points and measurement error based on latitude and longitude[J]. Geomatics & Spatial Information Technology, 2013, 36(11): 235-237.

[28] 邱德厚. 基于射线追踪技术的天波超视距雷达目标定位误差分析[J]. 数字技术与应用, 2016( 3): 45- 47.

    Qiu DH. Analysis of target position error of skywave over-the-horizon radar based on ray tracing method[J]. Digital Technology & Application, 2016( 3): 45- 47.

[29] 谢锐, 万显荣, 赵志欣, 等. 外辐射源天地波雷达定位方法及精度分析[J]. 电波科学学报, 2014, 29(3): 442-449.

    Xie R, Wan X R, Zhao Z X, et al. Localization method and accuracy analysis in hybrid sky-surface wave passive radar[J]. Chinese Journal of Radio Science, 2014, 29(3): 442-449.

宋萍, 刘以安. 基于改进蜻蜓算法的多基地天波雷达定位模型[J]. 激光与光电子学进展, 2018, 55(11): 112001. Ping Song, Yian Liu. Multi-Static Sky-Wave Over-the-Horizon Radar Location Model Based on Improved Dragonfly Algorithm[J]. Laser & Optoelectronics Progress, 2018, 55(11): 112001.

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